Our goal in this project is to validate innovations in MRI to improve the characterization of carotid plaque and ultimately improve the management of carotid disease. Atherosclerotic disease of the carotid artery is the direct cause of 173,000 or approximately 25% of the nearly 690,000 ischemic strokes each year in the United States. However, current risk stratification based on percent stenosis provides very little patient specific information on the actual risk of stroke for most veterans with carotid disease. Within the VA system during the past 4-years, over 15,000 veterans underwent surgical treatment for asymptomatic carotid stenosis. Prospective randomized studies have found that only 10% of these asymptomatic patients will have a stroke within 5 years, and the significant majority will never have a cerebrovascular event. Although percent carotid stenosis is a well-established marker used to stratify patients to medical treatment or surgery, this method is only moderately sensitive, nonspecific, and limited in its ability to predict future stroke. Using MRI techniques that can image plaque surface morphology and composition, prospective longitudinal studies suggest that carotid inflammation, intraplaque hemorrhage (IPH) and plaque luminal surface disruption (disruption of fibrous cap (FC)) are associated with an increased risk of cerebral ischemic events. Although promising, the accuracy of these studies is limited by the small size of important plaque features, the depth of the artery, patient motion, and the general limitations of the MRI techniques used. In this project we will evaluate newly developed 3D MRI acquisition methods that are specifically designed to improve the detection and characterization of these important plaque details. Faster imaging coupled with methods to detect and eliminate motion-corruption will achieve a marked increase in in-vivo spatial resolution and clarity of plaque components. The combination of high-resolution 3D MRI, motion detection and correction, and cardiac and respiratory variation identification and elimination will provide detail of plaque morphology at a resolution not previously available. By overcoming most sources of motion artifacts in carotid imaging, this work will reduce the failure rate of carotid MRI and increase the accuracy in assessment of fibrous cap, intraplaque hemorrhage, and inflammation. The swallow detection and image re-acquisition should eliminate or reduce major swallowing artifacts. By improving the visualization and description of plaque morphology, these methods should improve the detection and characterization of lesions that are at high risk of causing cerebral emboli. The ability to effectively triage carotid artery disease would be of significant benefit, providing reassurance to those without high-risk lesions that they can safely be treated without surgery while providing substantial support to the recommendation for intervention in those with unstable plaques.